A database of information on characterized fungal strains of Pyricularia, the genus name for a complex of species that cause blast symptoms on both leaves and reproductive organs of agriculturally important Poacea (eg. wheat blast) and grasses in general, including turfgrass.
The dashboard contains tabular and graphical elements for displaying information for each georeferenced strain, thus allowing to track temporal and spatial spread of species and host-specific lineages (or pathotypes) isolated from both wheat and grasses.
Pyblastr was created during the conduction of PhD research projects at the Plant Disease Epidemiology Laboratory (Dr. Del Ponte) in collaboration with Dr. Farman (University of Kentucky). The first version was released on February 2020 and is expected to be continuously updated.
Yes! definitely this is an open database that we would like to extend its utility by allowing other researches to contribution data to populate the global map. Get in touch (delponte@ufv.br) to receive instructions on how to participate and include the data in a Google sheets.
Reviews
Wheat blast diseases: danger on the move
Wheat blast: past, present and future
Wheat blast: from its origins in South America to its emergence as a global threatWebsites
Webinars
Open Wheat Blast Initiative
Cimmyt CABi
Wheat Blast: Epidemiology and management of an emerging global threat. Dr. Cruz
Symptoms of Wheat Blast Under Controlled Conditions, P.K. Malaker
Wheat blast infected field in Bangladesh, 2017. Dr. Malaker
Enjoy our project!
Under development.
---
title: " "
output:
flexdashboard::flex_dashboard:
source_code: embed
theme: united
social: menu
css: style2.css
logo: logo.png
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(
echo = FALSE,
message = FALSE,
warning = FALSE
)
library(flexdashboard)
library(prettydoc)
library(readxl)
library(tidyverse)
library(crosstalk)
library(plotly)
library(viridis)
library(gsheet)
library(leaflet.providers)
library(leaflet)
library(DT)
library(cowplot)
```
```{r load data, message=FALSE, warning=FALSE, include=FALSE}
Sys.setlocale("LC_ALL", "pt_BR.UTF-8")
mg_prod <- gsheet2tbl("https://docs.google.com/spreadsheets/d/13xAflAQ-x78Vkq0O0jUEkUxHPq5G1R4gwqzillMxoTo/edit?usp=sharing")
wb1 <- gsheet2tbl("https://docs.google.com/spreadsheets/d/1x3KKDGIwdPQdG3YE5Ekn1iExMrqV76ndJbXAgLe7dsA/edit?usp=sharing")
wb2<- gsheet2tbl("https://docs.google.com/spreadsheets/d/1W5nJWJwQJRKyUfWeiQNNA2xdQUsbEeCX6g6FH_i7i4o/edit#gid=532754791")
wb_all <- wb2 %>%
filter(labcode != 0) %>%
mutate(id = case_when(
is.na(py_binomial) ~ "No",
TRUE ~ "Yes"
)) %>%
mutate(wheat = case_when(
host_binomial == "Triticum aestivum" ~ "Wheat",
TRUE ~ "Non-wheat"
))
wb_all <- wb_all %>%
dplyr::select(labcode, year, state_province, county_municipality, lat, lon, host_binomial, py_binomial, py_lineage, primer, seq_locus, wheat, DNA_extraction)
set.seed(1000)
wb_all$lat <- round(jitter(wb_all$lat, factor = 1, amount = 0.001), 4)
wb_all$lon <- round(jitter(wb_all$lon, factor = 1, amount = 0.001), 4)
```
```{r all table, echo=FALSE}
sd <- SharedData$new(wb_all)
```
Dashboard
============
Column {.sidebar}
-------------------------------------
### Quick filter
```{r}
filter_slider("year", "Select years", sd, ~year)
filter_checkbox("wheat", "Host group", sd, ~wheat, inline = TRUE)
filter_select("host", "Host binomial", sd, ~host_binomial)
filter_checkbox("DNA_extraction", "DNA extracted?", sd, ~ DNA_extraction, inline = TRUE)
filter_select("py_species", "Pyricularia sp.", sd, ~py_binomial)
```
Column {.tabset}
-------------------------------------
### Map strains
```{r}
library(RColorBrewer)
library(htmltools)
pal <- colorFactor("Set2", domain = c("Wheat", "Non-wheat"))
leaflet(data = sd, width = "100%") %>%
# setView(-46.8, -20.40, zoom = 7) %>%
addProviderTiles("Esri.WorldImagery", group = "Aerial") %>%
addProviderTiles("OpenTopoMap", group = "Terrain") %>%
addScaleBar("bottomright") %>%
addProviderTiles(providers$CartoDB.Voyager, group = "Default") %>%
addLayersControl(
baseGroups = c("Default", "Aerial", "Terrain"),
overlayGroups = "Blast pathogen",
options = layersControlOptions(collapsed = T)
) %>%
addCircleMarkers(
group = "wheat",
radius = 6,
fillOpacity = 1,
weight = 0.5,
label = paste(wb_all$host, "- Details"),
fillColor = ~ pal(wheat),
popup = paste(
"Isolate details
",
"Code:", wb_all$"labcode", "
",
"Host:", wb_all$"host_binomial", "", "
",
"City:", wb_all$"county_municipality", "
",
"Year:", wb_all$"year", "
",
"DNA extraction:", wb_all$"DNA_extraction", "
",
"Species:", wb_all$"py_binomial", "
",
"Lineage:", wb_all$"py_lineage", "
"
)
) %>%
addLegend("bottomleft",
pal = pal,
values = ~wheat,
title = "Host",
opacity = 1
) %>%
addMeasure(
position = "bottomleft",
primaryLengthUnit = "meters",
primaryAreaUnit = "sqmeters",
activeColor = "#3D535D",
completedColor = "#7D4479") %>%
addEasyButton(easyButton(
icon="fa-globe", title="Zoom to Level 3",
onClick=JS("function(btn, map){ map.setZoom(3); }")))
```
### View grid display
```{r}
datatable(sd,
extensions = c("Buttons", "ColReorder"),
escape = TRUE, rownames = FALSE,
class = "cell-border stripe",
options = list(
dom = "Bfrtip", buttons = c("excel", "pdf"), deferRender = TRUE,
scrollY = 50,
pageLength = 15,
scroller = TRUE,
colReorder = TRUE
)
)
```
About this dashboard
============
Column {.sidebar}
-------------------------------------
### Participants
Dr. Emerson Del Ponte
MSc. João Ascari
MSc. Ignácio Cazón
Dr. Mark Farman
Column {.tabset}
-------------------------------------
### About this project
What is Pyblastr?
> A database of information on characterized fungal strains of Pyricularia, the genus name for a complex of species that cause blast symptoms on both leaves and reproductive organs of agriculturally important Poacea (eg. wheat blast) and grasses in general, including turfgrass.
What is it useful for?
>The dashboard contains tabular and graphical elements for displaying information for each georeferenced strain, thus allowing to track temporal and spatial spread of species and host-specific lineages (or pathotypes) isolated from both wheat and grasses.
Who are we?
>Pyblastr was created during the conduction of PhD research projects at the Plant Disease Epidemiology Laboratory (Dr. Del Ponte) in collaboration with Dr. Farman (University of Kentucky). The first version was released on February 2020 and is expected to be continuously updated.
May I contribute data?
>Yes! definitely this is an open database that we would like to extend its utility by allowing other researches to contribution data to populate the global map. Get in touch (delponte@ufv.br) to receive instructions on how to participate and include the data in a Google sheets.
Key wheat blast resources
Reviews
[Wheat blast diseases: danger on the move](https://link.springer.com/article/10.1007/s40858-017-0159-z)
[Wheat blast: past, present and future](https://www.annualreviews.org/doi/abs/10.1146/annurev-phyto-080417-050036)
[Wheat blast: from its origins in South America to its emergence as a global threat](https://bsppjournals.onlinelibrary.wiley.com/doi/full/10.1111/mpp.12747)
Websites
[Open Wheat Blast Initiative](http://openwheatblast.net/)
[Cimmyt](https://www.cimmyt.org/news/what-is-wheat-blast/) [CABi](https://www.cabi.org/isc/datasheet/121970)
Webinars
[Wheat Blast: Epidemiology and management of an emerging global threat. Dr. Cruz ](https://www.youtube.com/watch?v=gf1UFz926og&t=1188s)
[Symptoms of Wheat Blast Under Controlled Conditions, P.K. Malaker](https://www.youtube.com/watch?v=9KfqahgmASE)
[Wheat blast infected field in Bangladesh, 2017. Dr. Malaker](https://www.youtube.com/watch?v=pnD3qCRruK8)
Enjoy our project!
### How to use it
Under development.